設(shè)計(jì)中使用的信號(hào)為 信息信號(hào)： signal=sin(2*pi*sl*n*T) 高頻噪聲： noise =0.5*sin(2*pi*ns1*n*T) 混合信號(hào)： x=(signal+noise) 其中sl=1000Hz，ns1=4500Hz，T=1/10000?；旌闲盘?hào)波形為濾波器輸入信號(hào)波形，信息信號(hào)波形為輸出信號(hào)波形，濾波器的效果為濾除兩個(gè)高頻噪聲。
上傳時(shí)間： 2016-05-08
上傳用戶：梅浩梅浩
jiaocao yongyu tongxingongcheng xinhao xuexi
上傳時(shí)間： 2016-06-07
上傳用戶：sz869
This report presents a tutorial of fundamental array processing and beamforming theory relevant to microphone array speech processing. A microphone array consists of multiple microphones placed at different spatial locations. Built upon a knowledge of sound propagation principles, the multiple inputs can be manipulated to enhance or attenuate signals emanating from particular directions. In this way, microphone arrays provide a means of enhancing a desired signal in the presence of corrupting noise sources. Moreover, this enhancement is based purely on knowledge of the source location, and so microphone array techniques are applicable to a wide variety of noise types. Microphone arrays have great potential in practical applications of speech processing, due to their ability to provide both noise robustness and hands-free signal acquisition.
標(biāo)簽： Microphone array Tutorial Array Signal Processing
上傳時(shí)間： 2016-06-12
上傳用戶：halias
We consider the problem of target localization by a network of passive sensors. When an unknown target emits an acoustic or a radio signal, its position can be localized with multiple sensors using the time difference of arrival (TDOA) information. In this paper, we consider the maximum likelihood formulation of this target localization problem and provide efficient convex relaxations for this nonconvex optimization problem.We also propose a formulation for robust target localization in the presence of sensor location errors. Two Cramer-Rao bounds are derived corresponding to situations with and without sensor node location errors. Simulation results confirm the efficiency and superior performance of the convex relaxation approach as compared to the existing least squares based approach when large sensor node location errors are present.
標(biāo)簽： 傳感器網(wǎng)絡(luò)
上傳時(shí)間： 2016-11-27
上傳用戶：xxmluo
A simple example of audio signal processing on TMS320VC5416 USB DSK board. Main source is contained in tone.c file, memory configuration - tonecfg.cmd. Folder docs/ contains useful docmentation on board, its components and libraries. The example's configuration is based on example "tone" from Code Composer Studio's 3.1 example for 5416 DSK.
標(biāo)簽： DSK-example 5416 TMS 320 VC
上傳時(shí)間： 2017-09-29
上傳用戶：wang1104014663
The 4.0 kbit/s speech codec described in this paper is based on a Frequency Domain Interpolative (FDI) coding technique, which belongs to the class of prototype waveform Interpolation (PWI) coding techniques. The codec also has an integrated voice activity detector (VAD) and a noise reduction capability. The input signal is subjected to LPC analysis and the prediction residual is separated into a slowly evolving waveform (SEW) and a rapidly evolving waveform (REW) components. The SEW magnitude component is quantized using a hierarchical predictive vector quantization approach. The REW magnitude is quantized using a gain and a sub-band based shape. SEW and REW phases are derived at the decoder using a phase model, based on a transmitted measure of voice periodicity. The spectral (LSP) parameters are quantized using a combination of scalar and vector quantizers. The 4.0 kbits/s coder has an algorithmic delay of 60 ms and an estimated floating point complexity of 21.5 MIPS. The performance of this coder has been evaluated using in-house MOS tests under various conditions such as background noise. channel errors, self-tandem. and DTX mode of operation, and has been shown to be statistically equivalent to ITU-T (3.729 8 kbps codec across all conditions tested.
標(biāo)簽： frequency-domain interpolation performance Design kbit_s speech coder based and of
上傳時(shí)間： 2018-04-08
上傳用戶：kilohorse
用matlab實(shí)現(xiàn)bpsk調(diào)制 用randi函數(shù)產(chǎn)生10000個(gè)0、1隨機(jī)數(shù)，對(duì)原信號(hào)signal進(jìn)行判斷， 若為0，則生成調(diào)制信息1，若為1，則生成調(diào)制信息-1，從而實(shí)現(xiàn)BPSK調(diào)制。
上傳時(shí)間： 2018-04-25
上傳用戶：yyqqyy
利用randi函數(shù)產(chǎn)生10000個(gè)0、1隨機(jī)數(shù)，對(duì)原信號(hào)signal進(jìn)行分類每?jī)蓚€(gè)相鄰隨機(jī)數(shù)作為新信息SIGNAL并進(jìn)行判斷，若為0，則生成調(diào)制信息1+i，若為1，則生成調(diào)制信息-1+i，若為2，則生成調(diào)制信息-1-i，若為3，則生成調(diào)制信息1-i，從而實(shí)現(xiàn)QPSK調(diào)制
上傳時(shí)間： 2018-04-25
上傳用戶：yyqqyy
The BTS5016SDA is a one channel high-side power switch in PG-TO252-5-11 package providing embedded protective functions. The power transistor is built by a N-channel vertical power MOSFET with charge pump. The design is based on Smart SIPMOS chip on chip technology. The BTS5016SDA has a current controlled input and offers a diagnostic feedback with load current sense and a defined fault signal in case of overload operation, overtemperature shutdown and/or short circuit shutdown.
上傳時(shí)間： 2019-03-27
上傳用戶：guaixiaolong
% Computation of ST-ZCR and STE of a speech signal. % % Functions required: zerocross, sgn, winconv. % % Author: Nabin Sharma % Date: 2009/03/15 [x,Fs] = wavread('so.wav'); % word is: so x = x.'; N = length(x); % signal length n = 0:N-1; ts = n*(1/Fs); % time for signal % define the window wintype = 'rectwin'; winlen = 201; winamp = [0.5,1]*(1/winlen);
標(biāo)簽： 短時(shí)過零率和短時(shí)能量
上傳時(shí)間： 2019-09-23
上傳用戶：minwenji
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